Light Detection And Ranging (LiDAR) systems are attractive for use in many applications, such as autonomous vehicles (e.g., automobiles, farm equipment, etc.), driver-assist systems (e.g., collision-avoidance systems, etc.), video-game controllers, virtual- and augmented-reality systems, and the like.
LiDAR is based on laser range finding technology, in which the position of an object in a detection region is determined by transmitting a pulse of light toward the detection region and determining the time at which a reflection of the light pulse off of the object is detected. The position of the object is estimated by the time-of-flight (TOF) of the optical pulse to and from the object.
For vehicular LiDAR, a three-dimensional local map around a vehicle is developed by performing laser range finding in several directions and elevations around the vehicle. This can be done in various ways, such as using arrays of laser sources and detectors, rotating a single laser source about an axis through the vehicle, or directing the output signal from a single source about the vehicle using a rotating mirror or prism, or a stationary reflective cone. For example, US Patent Publication No. 20110216304 describes a LiDAR system based on a vertically oriented array of emitter/detector pairs that are rotated about an axis to provide a 360° horizontal field-of-view (FOV) and vertical FOV of several tens of degrees.
To reduce the amount of optical power required for interrogating a detection region, some LiDAR systems employ a receiver that is based on Geiger-mode avalanche photodiodes (GmAPDs). A GmAPD is a special type of avalanche photodiode (APD), referred to as a single-photon detector (SPAD), that has such high sensitivity that it can detect the receipt of a single photon of light. To sample the detection region, the GmAPD is operated in “gated mode,” in which it is put into “Geiger mode” (i.e., “armed”) by biasing it at a voltage level above its breakdown voltage. When biased above this voltage, the absorption of a single photon gives rise to the generation of a single charge-carrier pair that induces the SPAD to spontaneously generate an avalanche current that is macroscopically detectable. At the end of the gating period, the SPAD is “disarmed” by reducing its bias voltage below its breakdown voltage, which quenches the avalanche current enabling the SPAD to be rearmed to detect the arrival of another photon. GmAPD-based LiDAR systems can have several advantages over other LiDAR systems, including higher sensitivity, smaller size, weight, and electrical power requirements. As a result, GmAPD-based LiDAR is particularly well suited for airborne mapping and surveillance applications, such as low-altitude foliage penetrating LiDAR. Examples of GmAPD-based LiDAR systems are described by Clifton, et al., in “Medium Altitude Airborne Geiger-mode Mapping LiDAR System,” Proc. of SPIE, Vol. 9465, pp. 946506-1-946506-8 (2015), as well as by Niclass, et al., in “Design and Characterization of a 256×64-pixel single-photon imager in CMOS for a MEMS-based laser scanning time-of-flight sensor,” Optics Express, Vol. 20, pp. 11863-11881 (2012), each of which is incorporated herein by reference.
In a typical prior-art GmAPD-based LiDAR system, the distribution of objects within the detection region (a.k.a., a “point-cloud image”) is generated in an image frame that includes a sequence of many detection frames. In each detection frame of the image frame, the same view of the detection region is scanned by interrogating it with an optical pulse and detecting the reflections of that pulse. Statistical methods are usually applied to the results obtained through the sequence of detection frames to mitigate the impact of noise. The start time of each detection frame is defined by the transmission of its respective optical pulse. At a time based on a priori knowledge of the distance between the transmitter and the beginning (i.e., closest point) of the detection region, the GmAPD is placed in Geiger mode (i.e., is “armed”) to enable it to detect a single photon. The GmAPD is gated such that it remains in Geiger mode for a period of time that is based on how long it takes for the optical pulse to transit the entire range of the detection region. At the end of the detection frame, which corresponds to a time based on the maximum range of the detection region, the GmAPD is taken out of Geiger mode (i.e., is “disarmed”) to disable its detection of a single photon. In other words, the GmAPD is operated in gated mode using a gating signal that enables it to selectively sample the entire range of the detection region in each detection frame.
The requirements for a LiDAR system used in automotive applications are quite challenging. For instance, the system needs to have a large FOV in both the horizontal and vertical directions, where the FOV is supported over a distance that ranges from a few centimeters to hundreds of meters (e.g., 300 m or more). Further, the system must have high resolution, as well as an ability to accommodate a changing environment that surrounds a vehicle that might be travelling at relatively high speed. As a result, the system needs to be able to update the simulated environment around the vehicle at a high rate. In addition, an automotive LiDAR system needs to operate with a high signal-to-noise ratio (SNR) over a wide range of ambient light conditions (e.g., daytime, nighttime, foggy, rainy, etc.) and over its entire operating distance (i.e., scan range).
Unfortunately, in both Gm-APD-based LiDAR systems and non-Geiger-mode LiDAR systems, SNR degrades with range (i.e., distance through the detection zone). As a result, approaches to mitigate noise are typically necessary. For example, as discussed above, an image frame in which an image of the detection region is generated will include the repetition of many detection frames of the same view. Statistical methods, such as averaging, thresholding, etc., are then applied to the output signals generated during these multiple detection frames to reduce the impact of noise (e.g., detection of solar-generated photons, spurious dark counts generated internally to the SPAD, etc.) that can reduce the SNR of the resultant image. Such approaches give rise to undesirable latency that degrades system performance, however.
The need for a low-cost, high-performance LiDAR system having high SNR throughout its scan range remains unmet in the prior art.